AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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603 papers
Preliminary insight into success factors related to project outcomes that can be found at the midpoint of the development projects are offered.
An indicative project success model for software engineering projects is proposed and evaluated empirically in a large multinational software corporation setting, showing the model provides a valuable tool for KIBS organizations to increase their capabilities in running successful projects as well as to find targets fo...
There is a notable difference in the way the tools are used between the experts working together and the experts mentoring the new developers that have just joined the team, and over time the difference between pairs of experts and mixed pairs working together becomes almost unnoticeable.
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A framework is developed for software product roadmapping and results revealed that organizations view the product roadmap mainly as a tool for strategic decision making as it aims at showing the future directions of the company's products.
The perception of the impact of agile methods is predominantly positive, and several challenge areas were discovered, but based on this study, agile methods are here to stay.
In this paper, we propose a method for predicting development effort based on user stories. Such approach is well suited for Agile software projects where requirements are developed along with the project and only sketched in a rough manner. We apply the proposed method to two industrial Agile software projects of very...
This paper examines the perceived benefits of cloud computing from the cloud users' perspectives using content analysis techniques and proposes that the empirical insights gained are valuable to both researchers and practitioners.
By identifying the barriers and strengths of agile deployment, the paper deepens understanding of this highly relevant but relatively under-researched phenomenon and contributes to the literature on agile deployment and software process improvement.
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
For decades, a fundamental question about the difficulty of computing in high-dimensional spaces has resisted proof. New research resolves this question, removing a major theoretical obstacle to understanding the efficiency of randomized algorithms used across science and computing. The Kannan–Lovász–Simonovits (KLS) conjecture was proposed in 1995. It asks whether, for a broad class of high-dimensional […] The post Solving a 31-year-old grand challenge in mathematics – the KLS conjecture appear…
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
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